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Reinforcement Learning Robotics Jobs in Seattle, WA

Cobot

AI Research Engineer

Seattle, WA · On-site

Develop and evaluate reinforcement learning algorithms and frameworks for autonomous behaviors ... While direct robotics manipulation experience is not required, familiarity with robotic systems or ...

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Reinforcement Learning Robotics information

What is reinforcement learning in robotics?

Reinforcement learning in robotics refers to a type of machine learning where robots learn to perform tasks through trial and error, receiving feedback from their actions in the form of rewards or penalties. This approach allows robots to autonomously develop complex behaviors by interacting with their environment, rather than relying solely on pre-programmed instructions. Reinforcement learning is especially useful for tasks that are difficult to model explicitly, such as walking, grasping, or navigation. Over time, the robot improves its performance by maximizing the cumulative reward, leading to more efficient and adaptive behaviors.

What are some common challenges faced when implementing reinforcement learning algorithms in robotics projects?

One common challenge in this role is bridging the gap between simulation and real-world environments, as algorithms that perform well in simulation may not translate directly to physical robots due to unpredictable variables and hardware limitations. Additionally, ensuring the safety and stability of the robot during training is crucial, since trial-and-error learning can sometimes result in unintended behaviors or hardware damage. Collaboration with hardware engineers and domain experts is often necessary to fine-tune models, interpret results, and iterate on solutions. Overcoming these challenges requires patience, adaptability, and strong communication skills within a multidisciplinary team.

What are the key skills and qualifications needed to thrive as a reinforcement learning robotics engineer, and why are they important?

To thrive as a Reinforcement Learning Robotics Engineer, you need a strong background in robotics, machine learning, and programming, typically supported by a degree in computer science, engineering, or a related field. Expertise with frameworks like TensorFlow or PyTorch, experience with simulation environments (such as Gazebo or ROS), and familiarity with reinforcement learning algorithms are essential. Strong problem-solving skills, creativity, and effective communication set standout professionals apart in this rapidly evolving field. These skills enable engineers to develop intelligent robotic systems that adapt and learn efficiently, driving innovation and practical deployment in real-world environments.

What is the difference between Reinforcement Learning Robotics vs Machine Learning Engineer?

AspectReinforcement Learning RoboticsMachine Learning Engineer
Required CredentialsDegree in Robotics, Computer Science, or related fields; knowledge of reinforcement learningDegree in Computer Science, Data Science, or related fields; expertise in machine learning algorithms
Work EnvironmentRobotics labs, manufacturing, autonomous systemsTech companies, data-driven projects, software development
Industry UsageAutonomous robots, industrial automation, researchData analysis, predictive modeling, AI applications

Reinforcement Learning Robotics focuses on applying reinforcement learning techniques to control and optimize robotic systems, often in physical environments. Machine Learning Engineers develop algorithms for a broad range of applications, including data analysis and predictive modeling. While both roles require knowledge of machine learning, Reinforcement Learning Robotics emphasizes robotics and real-world interaction, whereas Machine Learning Engineers work across various industries with software-based solutions.

What are popular job titles related to Reinforcement Learning Robotics jobs in Seattle, WA?

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The top searched job categories for Reinforcement Learning Robotics jobs in Seattle, WA are:

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Cities near Seattle, WA with the most Reinforcement Learning Robotics job openings:

Reinforcement Learning Robotics jobs near you

Member of Technical Staff, Microsoft Robotics (Robotics Simulation)

Microsoft

Redmond, WA • On-site

Full-time

Re-posted 24 days ago

Microsoft rating

8.5

Company rating: 8.5 out of 10

Based on 132 frontline employees who took The Breakroom Quiz

79th of 245 rated software companies

Job description

Overview
Microsoft's Discovery and Quantum (MDQ) division develops and delivers advanced artificial intelligence (AI), cloud-enabled capabilities, and strategic technologies to help solve the world's major challenges. From accelerating scientific discovery with advanced AI tools, to pioneering breakthroughs in quantum computing, to advancing robotics and AI capabilities that drive real-world impact, joining MDQ means building the future, partnering with fast-moving innovators, and operating in a high-impact, mission-driven environment.
At Microsoft Robotics within MDQ, we build and deploy technologies that enable people, robots, and AI agents to collaborate and achieve more.
We are building Microsoft's platform for physical intelligence-an integrated robotics software and AI platform that brings together humans, robots, and agents through robotics AI models, innovative teaming solutions and experiences, physically grounded agentic AI workflows, trustworthy test and evaluation, and real-world customer-focused validation. Built on Microsoft's core platforms and delivered through and with a global ecosystem of partners and customers, this platform accelerates AI for the physical world and helps robotics solutions move from experimentation to reliable, scaled deployment.
We are hiring a Member of Technical Staff, Microsoft Robotics (Robotics Simulation) at the Senior level, to lead the design, integration, and analysis of physics-based simulation frameworks that underpin robotics development, testing, and AI model training across Microsoft's robotics platform. This engineer will architect and optimize high-fidelity simulation environments that accurately model robot kinematics, dynamics, sensors, actuators, and contact physics, enabling reinforcement learning training, closed-loop policy evaluation, synthetic data generation, and sim-to-real transfer. The role bridges advanced physics simulation, robotics autonomy stacks, and large-scale ML infrastructure to accelerate the development and deployment of physically grounded AI.
Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
#MicrosoftRobotics #MDQ
Responsibilities
  • Design, develop, and maintain physics-based simulation frameworks for robotics applications, including accurate modeling of rigid-body dynamics, articulated mechanisms, contact and friction, deformable objects, and fluid interactions as required by target robot platforms.
  • Implement essential robotics simulation features, including accurate sensor models (cameras, LiDAR, IMUs, force/torque sensors, tactile arrays), actuator models, controller interfaces, and communication protocols that mirror real robot hardware behavior.
  • Build real-to-sim and sim-to-real workflows for dynamic environments and robotics tasks, implementing domain randomization, system identification, and physics parameter tuning to minimize sim-to-real gaps.
  • Create and maintain asset toolchains supporting industry-standard formats (USD, URDF, MJCF, SDF) and integrate with 3D content pipelines for environment and robot model ingestion.
  • Develop simulation infrastructure for robust autonomy test and evaluation, enabling the use of rigorous test methods and design of experiments for validation and verification-based of robotics technologies and algorithms.
  • Develop simulation infrastructure for robot learning policies, including reinforcement learning training at scale, with parallelized environment instances, reward instrumentation, curriculum management, and integration with distributed ML training frameworks.
  • Collaborate closely with robotics engineers, ML researchers, and platform engineers to enable large-scale robotics development, training pipelines, benchmarking suites, and automated evaluation workflows.
  • Lead architectural decisions for simulation platform selection, customization, and extension, evaluating and integrating engines such as MuJoCo, Isaac Sim, Gazebo, Genesis or proprietary solutions based on fidelity, performance, and scalability requirements.
  • Review product code and test code to ensure it meets team standards for simulation accuracy, performance, and maintainability, coaching and providing feedback to develop other engineers' skills.
  • Drive efforts to integrate logging and instrumentation for gathering telemetry data on simulation performance, fidelity metrics, and training pipeline health.
  • Remain current in simulation and physics engine developments-as well as emerging technologies such as physical world models-proactively evaluating new trends, technical solutions, and research advances, and assessing how to adapt them to the robotics platform.

Qualifications
Required Qualifications:
  • Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
    • OR equivalent experience.

Other Requirements:
  • Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:
    • Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.

Preferred Qualifications:
  • Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
    • OR Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
    • OR equivalent experience.
  • Extensive experience in physics simulation engineering, with demonstrated expertise in rigid-body dynamics, contact modeling, or real-time physics engines (e.g., MuJoCo, Newton, PhysX, Bullet, DART).
  • Experience with robotics simulation platforms such as Isaac Sim, MuJoCo, Gazebo, Drake, or equivalent, including sensor simulation and actuator modeling.
  • Proven background in 3D graphics, real-time rendering, or game engine development (Unity, Unreal, or proprietary engines).
  • Experience building sim-to-real transfer pipelines, domain randomization frameworks, or system identification workflows for robotic manipulation or locomotion.
  • Proficiency in Python and C++ with experience in distributed computing, GPU-accelerated simulation, or parallel environment management for RL training.
  • Familiarity with ML frameworks (PyTorch, JAX, TensorFlow) and their integration with simulation environments for end-to-end training pipelines.
  • Experience with asset pipeline toolchains supporting URDF, MJCF, USD, or OpenUSD formats for robot and environment model management.

Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200 - $261,000 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

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About Microsoft

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Our infrastructure is comprised of a large global portfolio of more than 100 datacenters and 1 million servers. Our foundation is built upon and managed by a team of subject matter experts working to support services for more than 1 billion customers and 20 million businesses in over 90 countries worldwide. With environmental sustainability and optimization at the forefront of our datacenter design and operations, we continue to grow and evolve as we meet the ever-changing business demands that hold Microsoft as a world-class cloud provider.

Industry

Computer and computer peripheral equipment and software wholesalers

Company size

10,000+ Employees

Headquarters location

Redmond, WA, US

Year founded

1975

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